We investigated changes in primary schoolchildren's perceptions of the school climate amidst the COVID-19 pandemic and online learning shift. Data from the Modified-Delaware School Climate Survey-Student collected before (Time 1 (T1): October/November 2019) and during the pandemic's initial wave (Time 2 (T2): 12 months later) in Spain, Norway and Poland were analysed. In this repeat cross-sectional pre-post quasi-experimental study, we included a total of 1167 participants at T1 and 1209 participants at T2, ranging in age from 8 to 16 years and representing schoolchildren from fourth to last primary grades. Findings revealed a significant decline (overall OR = 0.80) in school climate perception across dimensions and countries during the pandemic's onset. Boys exhibited more negative perceptions than girls, particularly pronounced in Norway (OR = 0.59). Age also played a role, with a decline as students advanced in age, especially prominent in Poland (overall OR = 0.74). Our results emphasize the necessity of considering gender and age distinctions to enhance school climate during crises and proactively mitigate adverse effects on school climate.

Mari Gunnes; Sébastien Muller; Eva María Romera-Félix; Ida Laudańska-Krzemińska; Rocío Luque-González; Agata Wiza; Konstantinos Antypas. School climate during the COVID-19 pandemic in three European countries: A cross-sectional pre-post quasi experimental study. International Journal of Educational Research Open 2024, 7 .

Mari Gunnes, Sébastien Muller, Eva María Romera-Félix, Ida Laudańska-Krzemińska, Rocío Luque-González, Agata Wiza, Konstantinos Antypas. School climate during the COVID-19 pandemic in three European countries: A cross-sectional pre-post quasi experimental study. International Journal of Educational Research Open. 2024; 7 ():.

Mari Gunnes; Sébastien Muller; Eva María Romera-Félix; Ida Laudańska-Krzemińska; Rocío Luque-González; Agata Wiza; Konstantinos Antypas. 2024. "School climate during the COVID-19 pandemic in three European countries: A cross-sectional pre-post quasi experimental study." International Journal of Educational Research Open 7, no. : .

Gianluca Morciano; José Manuel Alcalde Llergo; Andrea Zingoni; Enrique Yeguas Bolívar; Juri Taborri; Giuseppe Calabrò. Use of recommendation models to provide support to dyslexic students. Expert Systems with Applications 2024, 249 .

Gianluca Morciano, José Manuel Alcalde Llergo, Andrea Zingoni, Enrique Yeguas Bolívar, Juri Taborri, Giuseppe Calabrò. Use of recommendation models to provide support to dyslexic students. Expert Systems with Applications. 2024; 249 ():.

Gianluca Morciano; José Manuel Alcalde Llergo; Andrea Zingoni; Enrique Yeguas Bolívar; Juri Taborri; Giuseppe Calabrò. 2024. "Use of recommendation models to provide support to dyslexic students." Expert Systems with Applications 249, no. : .

Multilabel classification as a data mining task has recently attracted increasing interest from researchers. Many current data mining applications address problems with instances that belong to more than one class. These problems require the development of new, efficient methods. Advantageously using the correlation among different labels can provide better performance than methods that manage each label separately. In recent decades, many methods have been developed to deal with multilabel datasets, which makes it difficult to decide which method is the most appropriate for a given task. In this paper, we present the most comprehensive comparison carried out so far. We compare a total of 62 different methods and several configurations of each one for a total of 197 trained models. We also use a large set of problems comprising 65 datasets. In addition, we studied the efficiency of the methods considering six different classification performance metrics. Our results show that, although there are methods that repeatedly appear among the top-performing models, the best methods are closely related to the metric used for evaluating the performance. We also analyzed different aspects of the behavior of the methods.

Nicolás E. García-Pedrajas; José M. Cuevas-Muñoz; Gonzalo Cerruela-García; Aida de Haro-García. A thorough experimental comparison of multilabel methods for classification performance. Pattern Recognition 2024, 151 .

Nicolás E. García-Pedrajas, José M. Cuevas-Muñoz, Gonzalo Cerruela-García, Aida de Haro-García. A thorough experimental comparison of multilabel methods for classification performance. Pattern Recognition. 2024; 151 ():.

Nicolás E. García-Pedrajas; José M. Cuevas-Muñoz; Gonzalo Cerruela-García; Aida de Haro-García. 2024. "A thorough experimental comparison of multilabel methods for classification performance." Pattern Recognition 151, no. : .